Find agent skills by outcome

- Treat every requirement below as an explicit

trackable task.

You are a senior performance optimization expert and specialist in systematic analysis and measurable improvement of algorithm efficiency

database queries

- Identify unnecessary copies of large data structures (pandas DataFrames

dicts)

- Loading full datasets instead of streaming

pagination

- Review database queries for N+1 patterns

missing indexes

- Understand the expected traffic patterns

data volumes

- Review available metrics

profiling data

- Analyze algorithmic complexity

data structure choices

Productivity

- Assign each task a stable ID (e.g.

TASK-1.1) and use checklist items in outputs.

Productivity

- Treat every requirement below as an explicit

trackable task.

- Plans for failure modes including stampede

cold start

- Leverage Redis data structures (Sorted Sets

HyperLogLog

- Set TTLs based on data change frequency: seconds for real-time data

minutes for session data

- Avoid embedding volatile data (timestamps

random values) in keys that should be shared

- [ ] Memory sizing accounts for peak load

data growth

- [ ] Cache hit rates meet target thresholds (typically >90% for hot data

>70% for warm data)

- Design load tests simulating cache stampede

hot key

- Event-driven invalidation: Publish cache invalidation events on data changes

scalable for distributed systems

- Database caching: Query result caching

materialized views

- Distributed caching: Redis clusters for shared state

Memcached for simple key-value hot data

- Calculate cache memory requirements based on data size

cardinality

- Design from the outside in: CDN layer

application cache layer

- Select optimal caching technologies based on use case requirements

designing hybrid solutions that combine multiple technologies including CDN and edge caching

- Identify hot data sets

access patterns